Lecture 12: Linear Regression with Multiple Variables

Question 1

If alpha of gradient descent is too ? => may never find the j minimum

Answer 1

If alpha of gradient descent is too big => may never find the j minimum

Question 2

If alpha is too ?, j (cost function ) will take forever to converge

Answer 2

If alpha is too small, j (cost function ) will take forever to converge

Question 3

Feature scaling:
Make sure features are on a ? scale:
e.g. x1 = size (0-2000 m2)
=> x1 = size (m2)/2000

Answer 3

Feature scaling:
Make sure features are on a similar scale:
e.g. x1 = size (0-2000 m2)
=> x1 = size (m2)/2000

Question 4

Mean normalisation:
Replace x_i with (??) with to make features have approximately ? mean
(Do not apply to x0 = 1 ).
e.g. x1 =  size (0-2000 m2)
=> x1 = (size - 1000 )/ 2000

Answer 4

Mean normalisation:
Replace x_i with (x_i - Mean_i) with to make features have approximately zero mean
(Do not apply to x0 = 1 ).
e.g. x1 =  size (0-2000 m2)
=> x1 = (size - 1000 )/ 2000